The GEQO module is intended
for the solution of the query optimization problem similar to a
traveling salesman problem (TSP). Possible query plans are encoded as
integer strings. Each string represents the join order from one
relation of the query to the next. E. g., the query tree

/\
/\ 2
/\ 3
4 1

is encoded by the integer string '4-1-3-2', which means, first
join relation '4' and '1', then '3', and then '2', where 1, 2, 3,
4 are relation IDs within the PostgreSQL optimizer.

Parts of the GEQO module
are adapted from D. Whitley's Genitor algorithm.

Specific characteristics of the GEQO implementation in PostgreSQL are:

Usage of a steady stateGA (replacement of the
least fit individuals in a population, not whole-generational
replacement) allows fast convergence towards improved query
plans. This is essential for query handling with reasonable
time;

Usage of edge recombination
crossover which is especially suited to keep edge losses
low for the solution of the TSP by means of a GA;

Mutation as genetic operator is deprecated so that no
repair mechanisms are needed to generate legal
TSP tours.

The GEQO module allows the
PostgreSQL query optimizer to
support large join queries effectively through non-exhaustive
search.

Work is still needed to improve the genetic algorithm
parameter settings. In file backend/optimizer/geqo/geqo_params.c, routines
gimme_pool_size and gimme_number_generations, we have to find a
compromise for the parameter settings to satisfy two competing
demands: